Recent studies have demonstrated that long non-coding RNAs (lncRNAs) are implicated in the regulation of tumor cell ferroptosis. However, the prognostic value of ferroptosis-related lncRNAs has never been comprehensively explored in glioma. In this study, the transcriptomic data and clinical information of glioma patients were downloaded from TCGA, CGGA and Rembrandt databases. We identified 24 prognostic ferroptosis-related lncRNAs, 15 of which (SNAI3-AS1, GDNF-AS1, WDFY3-AS2, CPB2-AS1, WAC-AS1, SLC25A21-AS1, ARHGEF26-AS1, LINC00641, LINC00844, MIR155HG, MIR22HG, PVT1, SNHG18, PAXIP1-AS2, and SBF2-AS1) were used to construct a ferroptosis-related lncRNAs signature (FRLS) according to the least absolute shrinkage and selection operator (LASSO) regression. The validity of this FRLS was verified in training (TCGA) and validation (CGGA and Rembrandt) cohorts, respectively. The Kaplan-Meier curves revealed a significant distinction of overall survival (OS) between the high- and low-risk groups. The receiver operating characteristic (ROC) curves exhibited robust prognostic capacity of this FRLS. A nomogram with improved accuracy for predicting OS was established based on independent prognostic factors (FRLS, age, and WHO grade). Besides, patients in the high-risk group had higher immune, stroma, and ESTIMATE scores, lower tumor purity, higher infiltration of immunosuppressive cells, and higher expression of immune checkpoints. Patients in the low-risk group benefited significantly from radiotherapy, while no survival benefit of radiotherapy was observed for those in the high-risk group. In conclusion, we identified the prognostic ferroptosis-related lncRNAs in glioma, and constructed a prognostic signature which was associated with the immune landscape of glioma microenvironment and radiotherapy response.

5-Methylcytosine (m5C) methylation is a significant post-transcriptional modification that play a crucial role in the development and progression of numerous cancers. Whereas the functions and molecular mechanisms underlying m5C methylation in gliomas remain unclear. This study dedicated to explore changes of m5C levels and the clinical significance of the m5C writer NSUN4 in gliomas. We found that high m5C levels were negatively related to prognosis of patients with glioma. Moreover, gain- and loss-of-function experiments revealed the role of NSUN4 in enhancing m5C modification of mRNA to promote the malignant progression of glioma. Mechanistically speaking, NSUN4-mediated m5C alterations regulated ALYREF binding to CDC42 mRNA, thereby impacting the mRNA stability of CDC42. We also demonstrated that CDC42 promoted glioma proliferation, migration, and invasion by activating the PI3K-AKT pathway. Additionally, rescue experiments proved that CDC42 overexpression weaken the inhibitory effect of NSUN4 knockdown on the malignant progression of gliomas in vitro and in vivo. Our findings elucidated that NSUN4-mediated high m5C levels promote ALYREF binding to CDC42 mRNA and regulate its stability, thereby driving the malignant progression of glioma. This provides theoretical support for targeted the treatment of gliomas.

Objective: The purpose of this study was to develop and validate a nomogram combined multiparametric MRI and clinical indicators for identifying the WHO grade of meningioma. Materials and methods: Five hundred and sixty-eight patients were included in this study, who were diagnosed pathologically as having meningiomas. Firstly, radiomics features were extracted from CE-T1, T2, and 1-cm-thick tumor-to-brain interface (BTI) images. Then, difference analysis and the least absolute shrinkage and selection operator were orderly used to select the most representative features. Next, the support vector machine algorithm was conducted to predict the WHO grade of meningioma. Furthermore, a nomogram incorporated radiomics features and valuable clinical indicators was constructed by logistic regression. The performance of the nomogram was assessed by calibration and clinical effectiveness, as well as internal validation. Results: Peritumoral edema volume and gender are independent risk factors for predicting meningioma grade. The multiparametric MRI features incorporating CE-T1, T2, and BTI features showed the higher performance for prediction of meningioma grade with a pooled AUC = 0.885 (95% CI, 0.821–0.946) and 0.860 (95% CI, 0.788–0.923) in the training and test groups, respectively. Then, a nomogram with a pooled AUC = 0.912 (95% CI, 0.876–0.961), combined radiomics score, peritumoral edema volume, and gender improved diagnostic performance compared to radiomics model or clinical model and showed good calibration as the true results. Moreover, decision curve analysis demonstrated satisfactory clinical effectiveness of the proposed nomogram. Conclusions: A novel nomogram is simple yet effective in differentiating WHO grades of meningioma and thus can be used in patients with meningiomas. Clinical relevance statement: We proposed a nomogram that included clinical indicators and multi-parameter radiomics features, which can accurately, objectively, and non-invasively differentiate WHO grading of meningioma and thus can be used in clinical work. Key Points: • The study combined radiomics features and clinical indicators for objectively predicting the meningioma grade. • The model with CE-T1 + T2 + brain-to-tumor interface features demonstrated the best predictive performance by investigating seven different radiomics models. • The nomogram potentially has clinical applications in distinguishing high-grade and low-grade meningiomas.

Background: Glioblastoma multiforme (GBM)is a highly aggressive malignancy of the central nervous system characterized by poor survival rates. Ferroptosis, an iron‐dependent cell death pathway, is a promising therapeutic target for GBM. However, current treatments targeting cell death pathways have not yielded expected results. Long noncoding RNAs (lncRNAs) have been implicated in tumour proliferation, however, their role in ferroptosis in GBM remains underexplored. This study investigated the interplay between the lncRNA LINC01088 and ferroptosis in GBM to identify novel therapeutic strategies.Methods: We conducted gain‐ and loss‐of‐function studies to assess the impact of LINC01088 on GBM tumourigenesis and ferroptosis both in vitro and in vivo. Bioinformatics, dual‐luciferase reporter assays, chromatin immunoprecipitation, RNA pulldown, mass spectrometry, RNA immunoprecipitation (RIP), and transcriptome sequencing were utilized to elucidate the mechanisms underlying LINC01088 expression and its downstream effects on ferroptosis.Results: The transcription factor specificity protein 1 (SP1) was identified as the promoter of LINC01088 transcription, which facilitated GBM progression. LINC01088 was found to inhibit ferroptosis and promote malignancy. Mechanistically, LINC01088 stabilized HLTF by enhancing its interaction with USP7 and preventing ubiquitin‐mediated degradation. The stabilization of HLTF led to the upregulation of SLC7A11, which inhibits ferroptosis in GBM. Rescue experiments confirmed that altering HLTF levels reversed the ferroptotic phenotypes associated with LINC01088 modulation.Conclusion: This study revealed a novel SP1/LINC01088/HLTF/USP7/SLC7A11 axis that regulates ferroptosis in GBM, highlighting LINC01088 as a potential therapeutic target for ferroptosis‐dependent GBM treatment.Key points: LINC01088 is transcriptionally upregulated by SP1. LINC01088 acts as a scaffold platform to bind USP7 and HLTF. USP7, as a deubiquitinating enzyme of HLTF, participates in inhibiting the ubiquitin‐proteasome degradation of HLTF. HLTF transcriptionally upregates the expression of downstream SLC7A11, and ferroptosis of GBM cells was inhibited.

Increasing evidences have revealed that N⁶‐methyladenosine (m⁶A) RNA methylation regulators participate in the tumorigenesis and development of multiple tumors. So far, there has been little comprehension about the effects of m⁶A RNA methylation regulators on lower‐grade gliomas (LGG). Here, we systematically investigated the expression profiles and prognostic significance of 36 m⁶A RNA methylation regulators in LGG patients from the TCGA and CGGA databases. Most of the m⁶A RNA methylation regulators are differentially expressed in LGG tissues as compared with normal brain tissues and glioblastoma (GBM) tissues. The consensus clustering for these m⁶A RNA methylation regulators identified three clusters. Patients in cluster 3 exhibited worse prognosis. In addition, we constructed an m⁶A‐related prognostic signature, which exhibited excellent performance in prognostic stratification of LGG patients according to the results of the Kaplan‐Meier curves, ROC curves, and univariate and multivariate Cox regression analyses. In addition, a significant correlation was observed between the m⁶A‐related prognostic signature and the immune landscape of the LGG microenvironment. The high‐risk group exhibited higher immune scores, stromal scores, and ESTIMATE scores but lower tumor purity and lower abundance of activated NK cells. Moreover, the expression level of immune checkpoints was positively correlated with the risk score. To conclude, the current research systematically demonstrated the prognostic roles of m⁶A RNA methylation regulators in LGG.